Comparison of pixel-based and object-oriented classification methods for land use mapping Using satellite image (Case Study: Ilam City)

Important factors in planning and urban management, especially in order to achieve sustainable development and optimal use of land in urban areas is the availability of timely and accurate information about the status of land use in urban areas. In this dirction, the aim of present study is to compare two methods of pixel-based and object-oriented classification in land use mapping with using ETM+ image in Ilam city, Ilam province using Idrisi Selva software. After the supply of related image and implementing geometric and radiometric corrections on image, we applied two classification methods to land use mapping. To assess the accuracy of classification methods, we used of indices of overall accuracy, kappa coefficient, producer accuracy and user accuracy. The results show that the object-oriented classification method has more resolution than the pixel-based classification method. The results of accuracy show that method of object-oriented in two indices of overall accuracy and kappa coefficient with (respectively) 94 percent and 91 percent was more accurate then pixel-based classification method with overall and Kappa coefficient 88 percent and 86 percent. The result of this study suggests that from object-oriented classification method use to production of land use map.